课程: Probability Foundations for Data Science

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Expectation

Expectation

课程: Probability Foundations for Data Science

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Expectation

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- [Presenter] In this chapter, you'll learn about measures of central tenancy, and spread and probability. In particular, you'll learn about expectation, variance, standard deviation, covariance, and correlation. The goal of this chapter is to help you solidify these fundamental concepts since they are heavily used throughout many other topics of probability that will be discussed in this course. Let's begin by exploring what expectation is, also known as expected value. Expectation is a measure of central tendency for a random variable. This means it is trying to find where the center of your probability is. This will be the main form of central tenancy you will focus on in this course, but note that you can find median and mode values for many of the topics that will be explored. The way you obtain the expectation is by getting the weighted average of all possible values a given random variable has. In this case, the weights are the corresponding probabilities for each given value…

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